Error analysis of calibration parameters estimation for binocular stereo vision system

Currently the research in binocular stereo vision area mainly focuses on camera calibration and stereo matching. For camera calibration, to estimate the camera's parameters is of vital very importance for acquiring better three-dimensional positioning reconstruction accuracy. This research investigates camera calibration parameters for a binocular stereo vision system and their effects on system reconstruction accuracy. Three different types of parameters and their effects on system reconstruction accuracy are probed with a semi-physical simulation. Firstly, a mathematic model is established and the major sources of parameter errors are analyzed for measuring system. Secondly, a semi-physical simulation system is developed to analyze the effects of parameter errors on the system reconstruction accuracy in the binocular stereo vision system. The binocular stereo vision system is treated as a black box. Three types of parameter errors (i.e., errors of the distortion parameter, camera internal and external parameters) are selected as input variables of the black box, and corresponding system reconstruction errors are regarded as output variables. The effects on the system reconstruction accuracy are analyzed using results of simulation. Finally, correlations between each of the three parameter errors and the system reconstruction error are analyzed, and influence on accuracy of the system is given. The results show that distortion parameter error has a minimal impact on system reconstruction accuracy and belongs to secondary factor. The impact of internal parameter error on system reconstruction accuracy is slightly larger, and correlation of them is linear. The external parameter error directly determines system reconstruction accuracy by affecting baseline distance and the angle between cameras.